{"id":"W4287393552","doi":"10.1287/mnsc.2022.4651","title":"Model-Free Assortment Pricing with Transaction Data","year":2023,"lang":"en","type":"article","venue":"Management Science","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Revenue management; Revenue; Transaction data; Computer science; Heuristic; Product (mathematics); Set (abstract data type); Database transaction; Dynamic pricing; Incentive; Integer (computer science); Transaction cost; Operations research; Econometrics; Mathematical optimization; Economics; Mathematical economics; Microeconomics; Mathematics; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001682414,0.0002245574,0.0001535007,0.001026051,0.0005989483,0.0006883407,0.002595481,0.00002224838,0.000121966],"category_scores_gemma":[0.00002654863,0.0001883301,0.00003255392,0.003511734,0.000214913,0.003631247,0.001856835,0.00009253336,0.0006793042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001173556,"about_ca_system_score_gemma":0.00001968442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001055127,"about_ca_topic_score_gemma":0.00009270695,"domain_scores_codex":[0.9968564,0.00000534537,0.0002495701,0.0009352051,0.001287968,0.0006655139],"domain_scores_gemma":[0.9979333,0.00001054615,0.0001352695,0.001827876,0.00006368842,0.0000293317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001732977,0.0005726906,0.009930743,0.001415857,0.0002763681,0.0003101669,0.0004053799,0.1754321,0.0008479827,0.4492092,0.2745465,0.08687977],"study_design_scores_gemma":[0.0008439633,0.0000167601,0.007953223,0.0000677362,0.0001094067,5.594833e-7,0.0009077237,0.8941875,0.00003564705,0.004206171,0.09127805,0.0003933383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1173465,0.00003321848,0.131013,0.01084063,0.001989055,0.002983183,0.00001730874,0.002916064,0.732861],"genre_scores_gemma":[0.9885618,0.00003172762,0.002372383,0.00257763,0.0002498756,0.00008641663,0.00008254564,0.00003774609,0.00599986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8712153,"threshold_uncertainty_score":0.8731308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06904066013616544,"score_gpt":0.2563709103046289,"score_spread":0.1873302501684635,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}